<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LLM Provider (E.g., OpenAI, Anthropic) on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/llm-provider-e.g.-openai-anthropic/</link><description>Recent content in LLM Provider (E.g., OpenAI, Anthropic) on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 21 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/llm-provider-e.g.-openai-anthropic/index.xml" rel="self" type="application/rss+xml"/><item><title>Build AI Agents with LangGraph</title><link>https://ai-blog.noorshomelab.dev/tutorials/build-ai-agents-with-langgraph/</link><pubDate>Thu, 21 May 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/tutorials/build-ai-agents-with-langgraph/</guid><description>&lt;p&gt;&lt;strong&gt;What you&amp;rsquo;ll build:&lt;/strong&gt; A functional and robust AI agentic system using LangGraph, capable of executing multi-step workflows and utilizing external tools.
&lt;strong&gt;Time needed:&lt;/strong&gt; ~90 minutes
&lt;strong&gt;Prerequisites:&lt;/strong&gt; Python 3.9+, Basic understanding of Large Language Models (LLMs), Familiarity with LangChain concepts (optional but helpful)
&lt;strong&gt;Version used:&lt;/strong&gt; v0.2&lt;/p&gt;
&lt;h2 id="introduction-to-langgraph-and-agentic-systems"&gt;Introduction to LangGraph and Agentic Systems&lt;/h2&gt;
&lt;p&gt;Welcome! In this tutorial, we&amp;rsquo;re going to dive into the exciting world of AI agents and learn how to build them using LangGraph. If you&amp;rsquo;ve ever found yourself wishing an AI could do more than just answer a single question, you&amp;rsquo;re in the right place.&lt;/p&gt;</description></item></channel></rss>